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Big Data Tool Predicts Best Lung Cancer Treatment

A doctor examines a lung x-ray.

Researchers at the National University of Singapore have developed a risk assessment tool that can predict survival rates and treatment outcomes of early-stage lung cancer patients.


National University of Singapore (NUS) researchers have developed a personalized risk assessment tool designed to predict the survival rate and treatment outcomes of early-stage lung cancer patients.

The tool relies on a panel of 29 unique extracellular matrix (ECM) genes that serve as biomarkers for the disease’s diagnosis and prognosis, based on their abnormal expression in lung cancers compared to healthy lung tissues.

The researchers focused on non-small cell lung cancer, the most common type of lung cancer.

The new tool successfully identified early-stage cancer patients who were able to increase their chances of survival through adjuvant chemotherapy.

"Our study demonstrates how we can harness and transform unprecedented amount of genomic data into a useful decision-making tool that can be implemented in routine clinical practice," says NUS's Lim Chwee Teck.

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Abstracts Copyright © 2018 Information Inc., Bethesda, Maryland, USA


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